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Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
ISTC-CC provides a listing of useful benchmarks for cloud computing.
Another list highlighting Open Source Software Releases.
Second GraphLab workshop should be even bigger than the first! GraphLab is a new programming framework for graph-style data analytics.
ISTC-CC Abstract
Heterogeneity and Dynamicity of Clouds at Scale:
Google Trace Analysis
ACM Symposium on Cloud Computing (SOCC'12), October 2012.
Charles Reiss, Alexey Tumanov*, Gregory R. Ganger*, Randy H. Katz,
Michael A. Kozuch^
University of California,
Berkeley
*Carnegie Mellon University
^Intel Labs
To better understand the challenges in developing effective cloudbased resource schedulers, we analyze the first publicly available trace data from a sizable multi-purpose cluster. The most notable workload characteristic is heterogeneity: in resource types (e.g., cores:RAM per machine) and their usage (e.g., duration and resources needed). Such heterogeneity reduces the effectiveness of traditional slot- and core-based scheduling. Furthermore, some tasks are constrained as to the kind of machine types they can use, increasing the complexity of resource assignment and complicating task migration. The workload is also highly dynamic, varying over time and most workload features, and is driven by many short jobs that demand quick scheduling decisions. While few simplifying assumptions apply, we find that many longer-running jobs have relatively stable resource utilizations, which can help adaptive resource schedulers.
FULL PAPER: pdf
